Trust Assessment
pamela-call received a trust score of 98/100, placing it in the Trusted category. This skill has passed all critical security checks and demonstrates strong security practices.
SkillShield's automated analysis identified 1 finding: 0 critical, 0 high, 0 medium, and 1 low severity. Key findings include Unpinned dependencies in installation instructions.
The analysis covered 4 layers: Manifest Analysis, Static Code Analysis, Dependency Graph, LLM Behavioral Safety. All layers scored 70 or above, reflecting consistent security practices.
Last analyzed on February 13, 2026 (commit 13146e6a). SkillShield performs automated 4-layer security analysis on AI skills and MCP servers.
Layer Breakdown
Security Findings1
| Severity | Finding | Layer | Location | |
|---|---|---|---|---|
| LOW | Unpinned dependencies in installation instructions The installation instructions for `@thisispamela/sdk` (JavaScript/TypeScript) and `thisispamela` (Python) do not specify a version. This practice can lead to non-reproducible builds and introduces a supply chain risk, as users will always install the latest version, which could potentially contain breaking changes or vulnerabilities introduced in future releases. It is a best practice to pin dependency versions for stability and security. Recommend pinning dependency versions in the installation instructions (e.g., `npm install @thisispamela/sdk@1.1.3` and `pip install thisispamela==1.1.3`) and advise users to utilize lock files (e.g., `package-lock.json`, `yarn.lock`, `requirements.txt`) for reproducible builds. | LLM | SKILL.md:30 |
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